code: def __call__(self, sample):
      img = sample["image"]
      mask = sample["label"]
      img = F.interpolate(  # NOTE: requires 4D
          img, scale_factor=self.scale, mode="bilinear"
      )
      # print("Scale:", img.shape, img.min(), img.max())
      # import ipdb; ipdb.set_trace()
      return {"image": img, "label": mask}
  
file_path: insightface/reconstruction/ostec/external/graphonomy/FaceHairMask/graphonomy_process.py
imports: import torch
  import torch.nn
  from torch.nn import functional
  from torchvision import transforms
label_desc: Use image node_id 2 for calling the Scale_only_img obj's underlying member method code with example usage: obj.__call__(sample) and returns: dict